This book is devoted to the econometric analysis of linear multivariate rational expectation models. It shows that the interpretation of multiplicity in terms of "new degrees of freedom" is consistent with a rigorous econometric reasoning. Non-uniqueness is the central theme of this book. Each chapter is concerned with a specific econometric aspect of rational expectations equilibria. The most constructive result lies in the possibility of an empirical determination of the equilibrium followed by the economy.

Macroeconomics is evolving in an almost dialectic fashion. The latest evolution is the development of a new synthesis that combines insights of new classical, new Keynesian and real business cycle traditions into a dynamic, stochastic general equilibrium (DSGE) model that serves as a foundation for thinking about macro policy. That new synthesis has opened up the door to a new antithesis, which is being driven by advances in computing power and analytic techniques. This new synthesis is coalescing around developments in complexity theory, automated general to specific econometric modeling, agent-based models, and non-linear and statistical dynamical models. This book thus provides the reader with an introduction to what might be called a Post Walrasian research program that is developing as the antithesis of the Walrasian DSGE synthesis.

Assumptions about how people form expectations for the future shape the properties of any dynamic economic model. To make economic decisions in an uncertain environment people must forecast such variables as future rates of inflation, tax rates, governme.

This theoretical work links a microeconomic model of imperfectly informed firms and unions in monopolistic competition to a general theory of wage and price setting in a macroeconomic model. The analysis is based on profit maximization and rational behavio

International experts have contributed to this volume in honor of Professor Karl A. Fox who has advanced the frontiers of economic science in many ways: by developing real-life applications of econometrics to agricultural economics and economic policy, by originating new concepts for understanding complex social systems, such as the education sector and functional economic areas, and by greatly extending the new discipline of eco-behavioral science, which deals with discrete units of social activity and its immediate environment called behavior settings.

What monetary policy framework, if adopted by the Federal Reserve, would have avoided the Great Inflation of the 1960s and 1970s? The authors use counterfactual simulations of an estimated model of the U.S. economy to evaluate alternative monetary policy strategies. The authors document that policymakers at the time both had an overly optimistic view of the natural rate of unemployment and put a high priority on achieving full employment. They show that in the presence of realistic informational imperfections and with an emphasis on stabilizing economic activity, an optimal control approach would have failed to keep inflation expectations well anchored, resulting in highly volatile inflation during the 1970s. Charts and tables.

Just as macroeconomic models describe the overall economy within a changing, or dynamic, framework, the models themselves change over time. In this text Stephen J. Turnovsky reviews in depth several early models as well as a representation of more recent models. They include traditional (backward-looking) models, linear rational expectations (future-looking) models, intertemporal optimization models, endogenous growth models, and continuous time stochastic models. The author uses examples from both closed and open economies. Whereas others commonly introduce models in a closed context, tacking on a brief discussion of the model in an open economy, Turnovsky integrates the two perspectives throughout to reflect the increasingly international outlook of the field. This new edition has been extensively revised. It contains a new chapter on optimal monetary and fiscal policy, and the coverage of growth theory has been expanded substantially. The range of growth models considered has been extended, with particular attention devoted to transitional dynamics and nonscale growth. The book includes cutting-edge research and unpublished data, including much of the author's own work.

Over the past two years, the IMF staff has been developing a new multicountry macroeconomic model called the Global Economy Model (GEM). This paper explains why such a model is needed, how GEM differs from its predecessor model, and how the new features of the model can improve the IMF’s policy analysis. The paper is aimed at a general audience and avoids technical detail. It outlines the motivation, structure, strengths, and limitations of the model; examines three simulation exercises that have been completed; and discusses the future path of GEM.

One of the major controversies in macroeconomics over the last 30 years has been that on the effectiveness of stabilization policies. However, this debate, between those who believe that this kind of policies is useless if not harmful and those who argue in favor of it, has been mainly theoretical so far. The Rational Expectation Hypothesis, Time-Varying Parameters and Adaptive Control wants to represent a step toward the construction of a common ground on which to empirically compare the two "beliefs" and to do this three strands of literature are brought together. The first strand is the research on time-varying parameters (TVP), the second strand is the work on adaptive control and the third one is the literature on linear stationary models with rational expectations (RE). The material presented in The Rational Expectation Hypothesis, Time-Varying Parameters and Adaptive Control is divided into two parts. Part 1 combines the strand of literature on adaptive control with that on TVP. It generalizes the approach pioneered by Tse and Bar-Shalom (1973) and Kendrick (1981) and one recently used in Amman and Kendrick (2002), where the law of motion of the TVP and the hyperstructural parameters are assumed known, to the case where the hyperstructural parameters are assumed unknown. Part 2 is devoted to the linear single-equation stationary RE model estimated with the error-in-variables (EV) method. It presents a new formulation of this problem based on the use of TVP in an EV model. This new formulation opens the door to a very promising development. All the theory developed in the first part to control a model with TVP can sic et simpliciter be applied to control a model with RE.

The introduction of a single European currency constitutes a remarkable instance of internationalization of monetary policy. Whether a concomitant internationalization can be detected also in the econometric foundations of monetary policy is the problem dealt with in this book. Its basic theoretical ingredients comprise a data-driven approach to econometric modelling and a generalized approach to cross-sectional aggregation. The resulting econometric model systematically combines statistical and economic theory by extending a cointegrated VAR into a structural ECM. The empirical outcome is a data-consistent causal money demand function, isolated within a properly identified dynamic macroeconomic system for Europe.